CHAPTER 3 

Effects of Proposed 

Alternatives on 

Aquatic Habitats and 

Native Fishes 

James R. Sedell 

Danny C. Lee 

Bruce E. Rieman 

Russell F. Thurow 

Jack E. Williams 
James R. Sedell is a research ecologist at the Pacific Northwest Forest and Research Experiment Station,

Forestry Sciences Laboratory, Corvallis, Oregon 97331.

Danny C. Lee is a research biologist at the Intermountain Forest and Research Experiment Station,

Forestry Sciences Laboratory, Boise, Idaho 83702.

Bruce E. Rieman is a research fisheries biologist at the Intermountain Forest and Research Experiment

Station, Forestry Sciences Laboratory, Boise, Idaho 83702.

Russell F. Thurow is a research fisheries biologist at the Intermountain Forest and Research Experiment

Station, Forestry Sciences Laboratory, Boise, Idaho 83702.

Jack E. Williams is a fisheries ecologist at the U.S. Department of Interior, Bureau of Land Management,

Columbia Northwest Technical Assistance Network, Boise, Idaho 83706.

436 Aquatics
TABLE OF 

CONTENTS 

Introduction 439 

Aquatic Viability Analysis: Species, Rationale, and Approach 440 

Step 1: Suitability of Proposed Alternatives for 

Aquatic Ecosystem Protection 442 

Riparian Widths and Activities 442 

Treatment of Strong and At-Risk Populations 444 

Treatment of Priority Watersheds and Category Watersheds 445 

Land Use and Management Activities 446 

Major Assumptions Needed to Determine Successful Evaluation Outcomes 446 

Ecosystem management standards 447 

Aquatic strategies standards 447 

Non-Federal Lands 449 

Summary and Comparison 449 

Step 2: Projected Effects on Widely-Distributed Salmonid Species 452 

Major Assumptions and Information Used to Judge Alternatives 452 

Classification trees 452 

Road distributions 456 

Ownership and management class 465 

Management activities 465 

Framework for Judging Alternatives 475 

Findings by Species 475 

Bull trout (Salvelinus confluentus) 476 

Westslope cutthroat trout (Oncorhynchus clarki lewisz) 479 

Yellowstone cutthroat trout (Oncorhynchus ¢larki bouvierz) 484 

Redband trout (Oncorhynchus mykiss ssp.) 487 

Steelhead trout ( Oncorhynchus mykiss mykiss) 492 

Stream-type chinook (Oncorhynchus tshawytscha) 499 

Ocean-type chinook (Oncorhynchus tshawytscha) 503 

Aquatics 
Step 3: Evaluation of Effects on Sensitive Species 504

General Assumptions and Information Base 504

Pacific lamprey (Lampetra tridentata) 504

Pit-Klamath brook lamprey (Lampetra lethophaga) 512

Lahontan cutthroat trout (Oncorhynchus clarki henshawf) 513

Pygmy whitefish (Prosopium coulter!} 513

Oregon Lakes tui chub (Gilo, bicolor oregonensis) 513

Leatherside chub (Gila copet) 514

Klamath Basin rare and sensitive fishes 514

Goose Lake sucker (Catostomus occidentalis lacusanserinus) and redband trout

(Oncorhynchus mykiss ssp.) in the Goose Lake Basin 515

Warner sucker (Catostomus warnerensis) and redband trout (Oncorhynchus mykiss ssp.)

in the Warner Basin 515

Wood River sensitive fishes 516

Malheur sculpin (Cottus bairdi ssp.) and redband trout (Oncorhynchus mykiss ssp.)

in the Harney Basin 517

Torrent sculpin (Cottus rhotheus) 518

Shorthead sculpin (Cottus confusus) 518

Margined sculpin (Cottus marginatus) 518

Aquatic Mollusk Species 519

Banbury Springs lanx (Lanx n. sp. 1) 519

Bliss Rapids springsnail (Taylorconcha serpenticola) 519

Desert valvata (Valvata utahensis) 519

Summary of Aquatic Habitats and Native Species Evaluation of Alternatives 520

References , 523

Appendix 3-A 527

Appendix 3-B 528

438 Aquatics
Introduction

The Aquatics and Riparian Science Teams analyzed the seven alternatives by evaluating their

effectiveness in sustaining aquatic ecosystem structure and function, and their expected effect on 25

taxa of native fishes. Our analysis focused on

alternatives as defined in Chapter 3 of the Preliminary Draft Environmental Impact Statements

(EISs) (USDA and USDI 1996a, 1996b).' The

analysis consisted of three steps. In step one, we

identified the level of protection, maintenance,

or restoration of aquatic and riparian habitats

offered by each alternative. In step two, we identified expected changes in distribution and status

of seven widely-distributed salmonid species that

would likely result from implementation of

each alternative. Step three involved a similar,

though less intensive, effort to identify expected

changes in the populations of 1 8 more narrowlydistributed fish species of special concern. Each

step built on the preceding one, as the sections

below demonstrate.

Our assessment is based on professional interpretation of both quantitative and qualitative information collected for the purpose of this evaluation

or generated as part of the broader scientific

assessment (Lee and others, in press). Participants

in the evaluation (evaluation team) included

Forest Service (FS) and Bureau of Land

Management (BLM) scientists from the Science

Integration Team (SIT) Aquatics Team that participated in the Broadscale Assessment of Aquatics

Species and Habitats (Lee and others, in press),

and additional invited scientists from the FS,

Environmental Protection Agency (EPA),

National Marine Fisheries Service (NMFS), and

U.S. Fish and Wildlife Service (USFWS) (appendix 3-A). Information relative to the alternatives

and individual fish species were prepared by the

SIT, Eastside EIS (EEIS) and Upper Columbia

River Basin EIS (UCRB) staffs and presented to

the evaluation team in a series of discussions held

at the Forestry Sciences Laboratory in Boise,

Idaho, on March 7 and 8, and 11 to 13, 1996.

The intent of the discussions was to explore issues

and probable outcomes associated with each alternative. A series of questions was developed by the

evaluation team and used to guide discussion

(described below). Notes taken during the discussion were used by the SIT aquatics team to frame

the issues and formulate the evaluation in this

report. The conclusions presented herein reflect

the consensus view of the SIT Aquatics Team that

participated in the evaluation.

Our analysis remains subjective in the sense that

to draw conclusions we filtered the anticipated

allocations and patterns of ground-disturbing and

restoration activities, and the current distribution

and status of fishes through our understanding of

the likely mitigative effects of each alternative.

Our analysis is based in existing data and spatial

patterns in those data. We believe any interpretations that must rationalize conclusions against

existing species distributions, patterns of disturbance, and relationships between the two cannot

strongly diverge from those we have made in our

analysis. In the time available for analysis, however,

we had the choice to either develop data and relationships on which to base our opinions or more

systematically develop opinions expressed without

the benefit of any detailed understanding or data.

We chose to draw conclusions from data and

relationships.

In our evaluation, we refer to two separate elements of a species' range, core and fringe. Core

areas refer to those portions of the species' distribution where there are concentrations of strong

populations (strongholds) and the species is well

distributed among adjacent watersheds and subbasins. Generally, such areas are found toward the

central part of the species' distribution, but may

'Analysis of the seven alternatives is based on the definitions found in the preliminary draft version of the Environmental Impact

Statements (February 1996). Detailed information cited in this chapter pertaining to the Preliminary Draft EIS is reproduced in

appendix I in Volume II of this document.

Aquatics 439
occur broadly across the Basin.2

 For anadromous

species with very few strong populations remaining, core areas are distinguished by large, contiguous blocks that are occupied by the species. For

example, the central Idaho subbasins of the

Salmon River would be considered core areas for

steelhead, even though populations are generally

depressed in that area. In general, we anticipate

that populations associated with the core(s) of a

species' distribution are most likely to persist in

the face of environmental change and disturbance

(Lee and others, in press). Strong populations generally support the full expression of life histories

including migratory forms, and are likely to be

more resilient than depressed populations or those

on the fringe of the species' range. We believe conservation of core areas is critical to species preservation, since these areas are most likely to persist

in the face of unforeseen environmental change. In

contrast, fringe areas refer to the portions of the

range that are on the periphery of the species'

range. Fringe areas are characterized by a relatively

small number of occupied watersheds that are

often isolated from the larger portions of the

species' range. Fringe areas are potentially important because they may include significant portions

of the genetic variability found in a species. The

core and fringe distributions considered in this

analysis are based on the distribution and status of

fishes as described in Lee and others (in press).

In the sections below, we describe each step in the

evaluation process. Within each step, we present

major assumptions and information used in the

evaluation, criteria or questions used to judge alternatives, major findings, and major uncertainties.

Aquatic Viability Analysis:

Species, Rationale, and

Approach

Our analysis of viability was directed exclusively at

fish by examining fish distribution and status, and

inferred habitat conditions as influenced by allocations and patterns of ground-disturbing and

restoration activities. The analysis consisted of two

parts. Part one addressed the viability of the seven

widely-distributed salmonids focused on in the

aquatics assessment (Lee and others, in press):

bull trout, redband trout, westslope and Yellowstone cutthroat trout, ocean-type and stream-type

chinook salmon, and steelhead trout. As discussed

in Lee and others (in press), these species are

viewed as important indicators of aquatic

integrity.

Part two focused on 18 of the 39 narrowlydistributed endemic or sensitive taxa that were

identified in Lee and others (in press) (table 3.1).

Some of these species are federally listed under the

Endangered Species Act of 1973 (ESA). Whether

listed or not, we omitted from analysis those taxa

that do not occur in more than one National

Forest or BLM District, since they are better

addressed by the individual administrative units.

We also omitted species for which Federal land

management has little or no perceived influence

on their viability.

We did not assess viability of desirable introduced

species because the distribution of introduced

species tends to be irregular. Viability is more of a

local issue that applies to individual populations

within small areas. It is not a broad-scale issue,

and there is little for our analysis to contribute.

Introduced species tend to persist wherever

humans choose to stock them.

Information on non-fish, aquatic organisms and

pertinent aspects of aquatic systems is limited,

and is often specific to an individual site. Many

aquatic invertebrates have very localized distributions, making effects of watershed-scale disturbance difficult to detect. For these reasons, we

decided it was inappropriate to address the nonfish, aquatic biota in a broad-scale evaluation of

alternatives.

The Basin is defined a those portions of the Columbia River basin inside the United States east of the crest of the Cascades and

those porions of the Klamath River basin and the Great Basin in Oregon.

448 Aquatics
Table 3.1. Rare and sensitive fish taxa in the Interior Columbia Basin Ecosystem Management Project

(ICBEMP) analysis areas. This list excludes seven widely-distributed salmonids that were focal species in

the Aquatics chapter of the Assessment of Ecosystem Components.' Viability analyses will be conducted only

on those 18 taxa occurring in more than one BLM/Forest Service jurisdiction and affected by land management activities.

ICBEMP Sensitive Fish Species

White sturgeon

Klamath lamprey

River lamprey

Pacific lamprey

Goose Lake lamprey

Pit-Klamath brook lamprey

Sockeye salmon

Chum salmon

Coho salmon

Coastal cutthroat trout

Lahontan cutthroat trout

Pygmy whitefish

Burbot

Sand roller

Northern roach

Alvord chub

Borax Lake chub

Callow tui chub

Oregon Lakes tui chub

Summer Basin tui chub

Sheldon tui chub

Mutton tui chub

Leatherside chub

Foskert speckled dace

Lost River sucker

Warner sucker

Goose Lake sucker

Shortnose sucker

Klamath largescale sucker

Wood River bridgelip sucker

Torrent sculpin

Shorthead sculpin

Pit sculpin

Slender sculpin

Margined sculpin

Wood River sculpin

Shoshone sculpin

Malheur sculpin

Sunapee char

Occur in more than one

BLM/FS jurisdiction?

Yes

No

Yes

Yes

No

Yes

Yes

Yes

Yes

No

Yes

Yes

Yes

Yes

No

No

No

No

Yes

No

No

No

Yes

No

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

No

Yes

Yes

Yes

No

Yes

No

Affected by land

management?

No

No

No

Yes

Yes

Yes

No

No

No

Yes

Yes

Yes

No

No

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

No

Yes

No

Viability

analysis?

No

No

No

Yes

No

Yes

No

No

No

No

Yes

Yes

No

No

No

No

No

No

Yes

No

No

No

Yes

No

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

No

Yes

Yes

Yes

No

Yes

No

'Lee, D.C.; Sedell, J.R.; Rieman, B.; [and others], (in press). Chapter 4. Broadscale assessment of aquatic species and habitats. In: Quigley,

Thomas M.; Arbelbide, S.J., tech. eds. An assessment of ecosystem components in the interior Columbia Basin and portions of the Klamath and

Great basins. Gen. Tech. Rep. PNW-GTR-XXX. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research

Station; (Quigley, Thomas M., tech. ed. The Interior Columbia Basin Ecosystem Management Project: scientific assessment).

Aquatics 441
Step 1: Suitability of

Proposed Alternatives for

Aquatic Ecosystem

Protection

The major elements of the aquatic conservation

strategy were evaluated on the basis of interim

widths of riparian areas and activities allowed

within them, treatment of strongholds and "atrisk" populations, treatment of priority watershed

or aquatic categories, amount of watershed and

riparian restoration, and major assumptions

needed to determine successful outcomes.

Riparian Widths and Activities

Current forest plans and forest practice rules regulate two major features of Riparian Habitat

Conservation Areas (RHCA) used in Alternatives

2, 3, and 7 and Riparian Management Areas

(RMA) used in Alternatives 4, 6, and parts of

Alternative 5: their width and the type and

amount of activities permitted to take place within them. Evaluating the effectiveness of RHCAs

and RMAs to protect and manage riparian areas is

difficult because of the complexity of the ecological functions they provide, the extended time over

which impacts can occur, and the often long duration it can take for ecosystems to recover. Four

biophysical principles underlie any evaluation of a

riparian management strategy: (1) the functions

and processes that govern production in a stream

are generally dependent on predictable and nearnatural energy and nutrient inputs; (2) wildlife

has a disproportionally high use of riparian areas

and stream-side forests compared with the overall

landscape; (3) small streams are generally more

affected by hill-slope activities than are larger

streams; and (4) as adjacent slopes become steeper,

the likelihood of disturbance resulting in discernable instream effects increases.

The width necessary to protect stream and riparian area structure and function at the small watershed level, and limits to disturbance near streams,

will necessarily be based on watershed and sitespecific analysis. The dimensions of riparian protection areas, particularly if they are to be used as

interim or default standards, could include safety

factors to allow for natural disturbances, uncertainties about the riparian ecosystem of interest,

and changes in public values (National Research

Council 1995). If an additional margin of error is

allowed (not unlike bridge design accounting for

unknown factors and longevity of structure), the

probability of habitat improvement becomes

greater and options for future management decisions are increased (FEMAT 1993, National

Research Council 1995).

Channelized flow from intermittent and small

streams into fish-bearing streams is a primary

source of sediment in mountainous regions (Belt

and others 1992). Gray (1970, 1978) identified

four mechanisms by which vegetation enhances

soil stability including: (1) mechanical reinforcement by roots; (2) regulation of soil moisture content; (3) buttressing between trunks or stems of

plants; and (4) surcharge from the weight of trees.

Gray and Megahan (1981) evaluated these hydromechanical effects in the Idaho batholith and

found that the first three are highly important in

stabilizing slopes, hollows, and intermittent

streams. Gray and Megahan (1981) recommended

using buffer zones along the margins of streams,

and establishment of vegetative-leave-areas in critical areas, such as hollows and intermittent

streams. Further, the assumption that large woody

debris (LWD) recruitment in streams comes only

from adjacent stream banks is not warranted given

that intermittent streams provide large quantities

of LWD during floods, after fires, and from debris

torrents (Reeves and others 1995). Many of these

small intermittent streams will not have full protection of ecological functions without an adequate RMA (Erman and Mahoney 1983, McGurk

andFong 1995).

The riparian goals and objectives of Alternatives 2

through 7, with the exception of the commodityemphasis areas of Alternative 5, are to protect and

restore riparian functions. The actual size of the

riparian areas depends on the local characteristics

that define them and a clear vision of how to

442 Aquatics
achieve the riparian management goals and objectives. Some of the goals of the aquatic conservation strategy for an alternative are to maintain the

function of instream processes over the life of the

plan and several additional decades. With the

exception of current forest plans (Alternative 1)

and the commodity-emphasis areas of Alternative

5, the alternatives utilize one-half to two maximum site potential tree heights3

 (90 ft or 27.4 m

for cold forest, 120 ft or 36.6 m for dry forest,

and 150 ft or 45.7 m for moist forest) depending

on stream size, plus the flood-prone (11 -year

floodplain) area or the 100-year floodplain,

whichever is greater, as a standard for defining

riparian widths.

Conservatively managed RHCAs and RMAs of

one maximum site potential tree height are likely

adequate to maintain most key riparian functions

(for example, stream shading, large woody debris

recruitment, small organic litter inputs, and nutrient regulation) throughout several decades or 100

years. The width dimensions of RHCAs and

RMAs in Pacific Anadromous Fish Strategy (PACFISH 1994) (Alternative 2) and the deviation

from PACFISH in Alternatives 3, 4, 6, 7, and

parts of Alternative 5 in general provide adequate

protection and a margin for error for riparian

processes critical for maintaining fish species in

most instances (FEMAT 1993; Lee and others, in

press; Murphy 1995; National Research Council

1995; PACFISH 1995). Alternatives 2, 3, and 7

use site potential tree height, 100-year floodplain

width, or a specified distance (50-300 ft or 15.2-

91.5 m depending on whether the stream is fishbearing and intermittent or permanently flowing).

Alternatives 4 and 6 use the same site potential

tree height standards as Alternatives 2, 3, and 7

with a minimum of 90 feet (27.4 m) for cold forest intermittent streams, to 300 feet or 91.5

meters (2 tree heights) for larger fish-bearing

streams in moist forests. The width is dependent

on potential vegetation type or one tree height to

two tree heights. In addition, the RMAs for

Alternatives 4 and 6 can vary depending on the

steepness of the adjacent slope; larger riparian

widths are defined where steep slope influences

occur. Generally, for slopes greater than 30 percent, RMAs will be wider than 300 feet (91.5 m).

Alternative 1 and the commodity-emphasis areas

of Alternative 5 do not adequately protect riparian

functions for several reasons. The existing forest

plans (Alternative 1) are highly variable in providing riparian protection. They frequently provide

no protection for intermittent streams, and generally do not fully protect riparian dependent functions (Lee and others, in press; Murphy 1995;

PACFISH 1995). In Alternative 5 timber and

livestock emphasis areas, which encompass nearly

all of eastern Oregon and the northern third of

the UCRB area, RMA widths vary from 20 feet

(6.1 m), to a maximum of one site potential tree

height, depending on the individual function or

combined functions that require protection. RMA

widths are the same as Alternatives 4 and 6 in

non-timber or livestock emphasis areas of the

Basin. While ecological functions of riparian areas

would be protected under Alternative 5, the alternative does not provide enough information to

evaluate whether a minimum or maximum width

would be used. The maximum width of one site

potential tree height leaves little margin for uncertainty, and less than one site potential tree height

would not provide full, direct ecological protection or have the possibility to provide for other

organisms with greater habitat requirements. The

variable widths of riparian areas suggest a onesize-fits-all approach of a maximum of one site

potential tree height will not accommodate all

organisms (PACFISH 1995). PACFISH (1995)

prescribed 90 me:ers (295 ft) minimum RHCA

widths for fish-bearing streams to maintain stream

function from non-channelized source sediment

inputs. A review of the literature indicates that the

minimum widths recommended by PACFISH

would also be sufficient to provide for other riparian functions with a margin for error (Belt and

3

Site potential tree height is defined as "the average maximum height of the tallest dominant trees (200 years or more) for a given

site class."

Aquatics 443
others 1992; Beschta and others 1987; Brazier

and Brown 1973; Gregory and others 1987; Lee

and others, in press; McDade and others 1990;

National Research Council 1995; Sedell and

Beschta 1991; Steinblums and others 1984).

There is no provision in commodity-emphasis

areas under Alternative 5 for protecting intermittent streams from which many disturbances originate (such as, landslides, sediment entry, and

woody debris recruitment; Belt and others 1992).

In addition, the watershed analysis procedure for

the commodity-emphasis areas under Alternative

5 is concerned primarily with hydrologic and geomorphic functions, and not ecosystem functions

of the landscape. In commodity-emphasis areas

under Alternative 5, only site-specific analysis is

required at the project scale, making it difficult to

determine cumulative effects at a watershed level.

A major assumption made under Alternatives 4,

5, and 6 is that active management of RMAs is

necessary to reduce fire severity. This would be

accomplished by recreating a mosaic of stands in

different conditions that offer natural firebreaks

and less concentrated food sources for pests,

mimicking historical forest conditions. The tradeoff between fire risk and the risks associated with

management activities is a watershed and sitespecific issue, and no clear direction is given for

the reconciliation of competing ecological needs

in the preliminary draft EIS standards and guidelines (see appendix I, Vol. II). While productivity

and fuel loading may be highest in the RMAs,

these zones are generally moister and historically

had longer fire return intervals (Agee 1994).

Thus, in an ecological sense, fire management

concerns are generally not a primary emphasis in

riparian zones. Although riparian corridors sometimes experienced high-intensity fires, the more

typical fire pattern was high-intensity fires that

burned down to the riparian corridors, decreased

in intensity, and often went out (Agee 1994).

Given the importance of the riparian area to fish

and aquatic habitat, a prudent course of treatment

benefiting both RMAs and the entire landscape

might be to treat the fire-prone portions of the

landscape outside of riparian areas. By focusing

treatment in areas adjacent to riparian zones, historical refuges within the RMAs would be protected, where activities occurring closer to the

stream have a greater probability for adverse

effects on the stream. Although break up of current continuity of fuels is a needed treatment over

much of the landscape, little is known about the

minimum threshold of treatment that would sufficiently reduce fuel loadings and thereby reduce

the potential for and frequency of major catastrophic fire. Historically, almost all of the lowseverity fire regimes were in a mosaic, "fire-safe"

condition (Agee 1994). If the upland landscape

can be restored to a more sustainable character

through thinning and prescribed burning, wildfires can be largely controlled before they burn

riparian zones.

For the purposes of this evaluation, we assumed

that the large tree standard contained in the interim RMA objectives and standards for Alternatives

4, 5, and 6 (see appendix I) takes precedence over

the fire regime and fire-severity standards applied

directly to riparian zones. In other words, if in a

dry forest type the RMAs were mostly composed

of mixed-age firs, then the big firs would generally

be of high ecological value and be in short supply

along streams and the RMAs would meet the silviculture standard for mature or late-successional

stage in zone 1. Thinning, from below (removing

the smaller, younger, understory trees), would

achieve the desired fire management goals (reducing fuel ladders) while also meeting the large tree

standards near streams; this is different from converting the entire area to a dry forest composition.

Treatment of Strong and At-Risk

Populations

Alternatives 3 through 6 do not specifically provide a mechanism for recognizing at-risk or critical habitats within subbasins other than those that

require watershed/ecosystem analysis. Although

conservation/restoration of strongholds for key

salmonids is an important and logical priority,

recognition and prioritization of other habitats

444 Aquatics
that support depressed populations of sensitive or

narrowly-distributed species is also important

in order to restore the condition of aquatic

ecosystems.

We could not identify any scheme for prioritizing

restoration activities in important but at-risk subwatersheds. For example, because the fringe distributions of several of the key salmonids are represented only by depressed populations and are not

in Category 1 watersheds,4 they would not require

watershed analysis. There appears to be no mechanism in any of the alternatives outside of the

intent to consider watersheds at risk. In guideline

A-G26 (Aquatics-Guideline 26; see appendix I), it

is suggested that managers (when prioritizing

watershed restoration activities) consider threatened and endangered species, important life histories, and riparian dependent species. We assumed

that there was no mechanism to prioritize protection of important and at-risk habitats or populations (such as depressed populations found in the

fringe distributions) if they did not coincide with

strong, Category 1, or priority watersheds. This

may be particularly significant for the fringe distributions of several species. Although fringe areas

may contribute a disproportionately large part of

the genetic diversity or variability for some

species, they are generally composed of depressed

populations that are not considered under the

strategies associated with any alternative.

Treatment of Priority Watersheds

and Category Watersheds

Priority watersheds in Alternative 2 are replaced

by watershed Categories 1", 2\ and 3(> in

Alternatives 3 through 6. Although the ecosystem

management alternatives require a mid-level (subbasin) analysis, the discussion does not clearly

acknowledge the uncertainty and limited utility of

the aquatic classification scheme. The classifications were intended to communicate broad-scale

issues and opportunities regarding conservation

and restoration potential of aquatic ecosystems,

not to develop a prescription (Lee and others, in

press). They are based on coarse data that have

not been verified. Examination of new and finerlevel information would likely result in many

modifications. A process for designating waterCategory 1 Watershed: These high integrity subbasins most closely resemble natural, fully functional aquatic ecosystems. In general they support large, often continuous blocks of high-quality habitat and watersheds with strong populations of multiple

species. Connectivity among watersheds and through the mainstem river corridor is unimpeded, and all life histories, including

migratory forms, are present and important. Native species predominate, though introduced species may be present. These subbasins provide a system of large, well-dispersed habitats resilient to large-scale disturbances. They provide the best opportunity for

long-term persistence of native aquatic assemblages and may be important sources for refounding other areas.

^Category 2 Watershed: These moderate integrity subbasins support important aquatic resources, and often have watersheds classified as strongholds for one or more species scattered throughout. The integrity of the fish assemblage is high or moderate. The

most important difference between Category 1 and Category 2 watersheds is increased fragmentation in Category 2 that has

resulted from habitat disruption or loss. These subbasins have numerous watersheds where native species have been lost or are at

risk. Connectivity among watersheds exists through the mainstem river system, or has the potential for restoration of life-history

patterns and dispersal among watersheds. Because these subbasins commonly fall in some of the more intensively managed landscapes, they may have extensive road networks. Stronghold watersheds that require conservative protection are scattered rather

than contiguous. These subbasins are more likely to provide opportunities to explore or experiment with watershed restoration

through active manipulation, or through attempts to produce more episodic disturbance followed by long periods of recovery.

''Category 3 Watershed: These low integrity subbasins may support populations of key salmonids or have other important aquatic

values, such as threatened and endangered species, narrow endemics, and introduced or hatchery supported sport fisheries. In general, however, these watersheds are strongly fragmented by extensive habitat loss or disruption throughout the component watersheds, and most notably through disruption of the mainstem corridor. Major portions or these subbasins are often associated with

private and agriculrural lands not managed by Forest Service or BLM. Although important and unique aquatic resources exist,

they are usually localized. Opportunities for restoring connectivity among watersheds, full expression of life histories, or other

large-scale characteristics of fully functioning and resilient aquatic ecosystems are limited or nonexistent in the near future.

Because the remaining aquatic resources are often strongly isolated, risks of local extinction may be high. Conservation of the

remaining productive areas may require a disproportionate contribution from federal management agencies, because these subbasins often include large areas of non-Federal land.

Aquatics 445
shed categories that can be amended through

mid-level analysis, however, is not provided. In

our evaluation we assumed that strongholds can

be identified and verified with subbasin analysis.

We also assumed that aquatic classification can be

amended and verified as well.

Land Use and Management

Activities

We assumed that harvest and thinning activities

have potentially negative net effects on aquatic

systems, and that prescribed burning, livestock

management, watershed restoration, and riparian

restoration have potentially positive net effects.

We recognize that these generalizations are not

true in all situations and within all subbasins.

Effects of timber harvesting and thinning are difficult to determine at the broad scale. However,

with the exception of helicopter logging, most

timber harvest activities have an ecological downside and higher risk potentials. This risk potential

stems from additional road, landing, and skid trail

soil compaction. Megahan and others (1992) concluded that new Best Management Practices

(BMPs) can reduce sediment yields compared to

historical practices, but risks of increased sedimentation from forest management practices will continue to occur if road building and timber harvesting take place. Menning and others (1996)

adapted a cumulative watershed effects accounting

system to model forest stand response to fire and

timber harvest activities. Their coefficients for different types of wildfires, timber harvest, grazing

activities, and roads reflect the relative associated

risk to watersheds from sedimentation and are

consistent with our assumptions.

We assumed that prescribed burning would not

require new roads or activities to effectively treat

the landscape and would result in no soil compaction. In reviewing literature on watersheds from

the western United States, Beschta (1990) concluded that where low-severity burns occur (as with

prescribed burning), much of the organic matter

comprising the forest floor may remain following

burning. In these situations, the effects of burning

are generally insignificant with regard to a wide

range of hydrologic and water quality variables.

Restoration may include a variety of activities that

influence aquatic habitats, but it is not possible to

determine the relative significance of those activities from their allocation in the alternatives.

Because restoration activities or the levels of those

activities are not clearly defined, we assumed that

restoration means significant progress in the

restoration of the processes and functions relevant

to aquatic habitats and species in the treatment

area. We generally assumed that more restoration

was better, and that moderate and high levels of

restoration in terms of acres or hectares treated per

decade (see "Major Assumptions and Information

Used to Judge Alternatives" section later in this

chapter) would produce positive trends in the status and distribution of a species. This assumption

would hold true as long as those activities were

subsequent to watershed/ecosystem analysis and

were distributed across a portion of the species'

range where they would be beneficial (for instance,

where the species is still present and capable of

responding). We also recognized that some risk is

inherent in all forest management and restoration

activities, and assumed that high restoration alternatives would be pursued with an approach that

maximizes learning while minimizing risks.

Major Assumptions Needed to

Determine Successful Evaluation

Outcomes

As established in the preliminary draft EISs, standards represent required actions, and guidelines

are suggestions for achieving objectives and are

not required actions (see appendix I for details).

Because we could not anticipate when guidelines

would or would not be followed, our analyses represent the outcomes associated with the situation

where they would generally not be followed. We

recognized that in some circumstances and in

some areas, guidelines would be implemented.

Many of the standards and guidelines in the interim RMAs appeared decoupled from the aquatic

conservation objectives. They referred to meeting

446 Aquatics
Riparian Management Objectives (RMOs) and

protecting RMAs but did not refer back to the

ecological objectives. We further assumed in our

analysis that the interim standards would become

final or long-term standards, since there was no

time period specified for analyzing watersheds and

the outcome of watershed analysis is unknown.

Ecosystem management standards

In Alternatives 3 through 7, ecosystem management planning is emphasized. As such, we

assumed that it would be completed or there

would be greater difficulty and uncertainty surrounding the management of landscapes and

cumulative effects. Our assumptions regarding

several important standards in the ecosystem management section of the preliminary draft EISs (see

appendix I) are as follows:

• EM-S127 (Develop and implement a standardized road condition and risk inventory.) We

assumed that it would be done within the first

one to two years or that the guideline for effective watershed restoration (a key element in our

evaluation) would be uncertain and the intent

of Alternatives 3 through 7 would not be met.

• EM-S13 (Construct new road crossings to maintain fish passage.) We assumed an ecosystem

management standard requires maintaining

hydrologic processes not just fish passages. As

such, the road's management standard in the

Aquatic Strategies Interim Objectives and

Standards section of the preliminary draft EISs

was assumed, specifically in areas where new

stream crossings would accommodate a 100-year

flood.

• EM-S 14 (Transportation plans should be developed in an integrated resource manner, supporting ecosystem analysis and prioritizing roads for

rehabilitation, closure, or obliteration.) We

assumed it would be done in the same timeframe or parallel to the above-mentioned

Standard EM-S 12.

• EM-S 15 (There shall be no net increase in road

density in any cluster. Road mileage increases

will be offset by an equal or greater mileage

decrease on a per cluster basis.) Subwatersheds

[6th hydrologic unit code (HUC)] through subbasins (4th HUC) are the appropriate scales to

relate the ecological and cumulative effects consistent with the ecosystem analysis requirements

presented in Alternatives 3 through 7. This is

the only place where a cluster is assigned a specific implementation requirement as opposed to

a strategic basin view. We assumed that there

was an ecological basis for reducing moderateto high-density roaded watersheds, but there

was no equal ecological basis for trading road

reduction in these areas for more roads in very

low-density or unroaded watersheds. Thus, we

assumed that a reduction in roads in high-density areas would not offset the negative effects of

increasing roads in low or unroaded areas.

• EM-S168 (Use adaptive management.) In order

for there to be an effective adaptive management program, we assumed that resources

would be allocated and priorities established, so

that road inventories, watershed analysis, and

design and implementation of inventory and

monitoring programs would be in place within

a two-year timeframe.

Aquatic strategies standards

Watershed and riparian restoration

management:

• A-S39 (Attainment and process for assessing

Proper Functioning Condition should be

7EM-S12 indicates Ecosystem Management - Standard, followed by the specific standard number cited (Chapter 3, Preliminary

Draft EISs) (USDA and USDI 1996a, 1996b).

"EM-S 16 indicates Ecosystem Management - Standard 15; Standard 15 was added to this evaluation of alternatives at a later date

than the other standards cited in this discussion and is therefore found in the August 1996 version of the Draft EIS.

''A-S3 indicates Aquatics - Standard, followed by the specific standard cited (Chapter 3, Preliminary Draft EISs) (USDA and

USDI 1996a, 1996b).

Aquatics 44?
required.) We assumed the attainment of proper

functioning condition (PFC) would be required

and that if it were not, management activities

would be modified to attain PFC. The PFC

concept is an example of a poorly-defined condition that is directed to be met, but for which

the preliminary draft EISs do not address the

ecological elements directly or specifically. We

have assumed that PFC addresses both the

hydrologic and geomorphic aspects of channels,

stream banks, and surface water as well as the

vegetative characteristics. Further, we have

assumed that PFC achieves hydrologic function

first and that the manager's decision-making

options are between achieving hydrologic function and attaining site-specific vegetation potential. For purposes of aquatic and terrestrial

organism communities, we assumed that vegetation standards are specifically included.

Conservation and restoration of PFC in riparian

areas includes managing toward an advanced

successional stage of riparian vegetation with

multiple species and age classes of woody vegetation. This is ecologically necessary. We further

assume that PFC is an interdisciplinary team

process; similar to watershed analysis, it will

likely require more than one person to complete

the analysis.

The PACFISH Recommended Livestock Grazing

Guidelines10 lists specific attributes of PFC, recommendations for modifying current directions,

and priorities for taking action. The specificity of

the guidelines provides a credible basis for evaluating and monitoring, and increases their ability for

implementation.

Monitoring and inventory:

• A-S7 (Regional and State offices shall develop

monitoring frameworks.) We assumed a monitoring program would be developed.

A-S8 (Regional and State offices should oversee,

ensure, and report results of monitoring programs.) We assumed regional and state offices

would oversee and ensure monitoring programs

and report their results.

A-S10 (Monitoring shall be conducted to determine if objectives are being met...If analysis

indicates that Watershed or Riparian

Management Objectives are not being met due

to natural conditions or to processes or action

outside of management control, then new objectives should be developed on the basis of new

information.) We thought that this was a standard that implied a cumulative watershed effects

(CWE) analysis. Currently only the Aquatics

Guideline A-G25 directly addresses CWE:

"Consider establishing qualitative and quantitative watershed disturbance (natural and management) levels or parameters for upland and riparian area zones to provide early indication of

potential watershed cumulative effects and

causal mechanisms for aquatic and riparian conditions." Alternative 7 is the only alternative

that directly addresses CWE by calling for a

consistent equivalent clearcut area (EGA) CWE

method and setting a 15 percent EGA threshold

which would trigger a watershed analysis

(McCammon 1993). This threshold is at a

watershed scale and does not distinguish nearstream disturbances from upslope disturbances

or set a lower threshold near streams than for

upslope areas. Alternatives 4 and 6 put forward

a riparian zoning scheme which sets the foundation for CWE determination that could be sensitive to spatial variations in considering watershed disturbing effects (McGurk and Fong

1995, Menning and others 1996). However,

only the vegetation management was directly

required as a standard (directing more riparian

forests toward mature and old forest condi-

'"Personal communication. May 24, 1995 [revised July 31, 1995]. John Lowe, U.S. Forest Service. Internal document on file

with: U.S. Department of Agriculture, Forest Service, U.S. Department of Interior, Bureau of Land Management, Interior

Columbia Basin Ecosystem Management Project, 112 E. Poplar, Walla Walla, WA. 99362.

448 Aquatics
tions). Developing disturbance limitation

criteria for each zone within the first couple of

years of a plan would help prorate CWE and

spatially locate these away from streams. All of

the alternatives would provide greater protection

for aquatic systems if they had such criteria.

Such a scheme would allow more creative solutions and proposed new activities to be developed for currently disturbed watersheds, because

planning models could be used before implementation of a project as opposed to instream

RMOs which are an after-the-project measure of

past events.

Key watersheds and watershed categories:

• A-S12 (Ecosystem analysis should be performed

in Category 2 and 3 watersheds before

Environmental Assessment (EA) or EIS required

activities, otherwise interims apply.) We

assumed ecosystem analysis would be conducted

in strongholds and high-priority watersheds in

Category 2 and 3 watersheds for Alternatives 3,

4, parts of Alternative 5, and 6.

Non-Federal Lands

No alternative addressed the role of non-Federal

lands in achieving the goals and objectives of the

aquatic conservation strategy. In assessing the role

of non-Federal land in the maintenance of fish

habitat and water quality, we assumed that the

federally managed lands would likely act as

anchors, and that, as important as non-Federal

land is to certain fishes and aquatic communities,

improvements would not be systematic throughout the Basin and conditions would not likely

improve substantially. We based this assumption

on the following reasons: (1) the goals of the

states' natural resource agencies generally are not

specifically aimed at restoring aquatic ecosystems

and biodiversity, but instead are aimed at meeting

societal needs while disrupting ecological processes and structures as little as possible; (2) as one

moves from the broad and uniform application of

forest practice rules, which are themselves not

fully protective of riparian function (FEMAT

1993, Murphy 1995, National Research Council

1995, Spence and others 1996) to rangelands and

then to settlement areas at the urban/wildland

interface, the outcomes of regulations and laws

are variable, localized and often vague; and (3)

adequate information about species in a site that

will be affected by management activity is generally lacking, especially in terms of the biological

condition and presence of rare species. While

each State within the Basin has goals associated

with their policies, the actual implementation of

those goals through adherence to the requirements embodied in the standards remains less

certain. For these reasons, we assumed the outcomes were highly uncertain and problematic for

such policies to protect and restore riparian and

aquatic resources through time. Private lands

affect corridors, low- to mid-elevation watersheds, valleys, and meadows. All of these are

important to different aquatic communities and

to water quality. Private land ownership patterns

afford Federal managers the opportunity to cooperate in maintaining and restoring of aquatic

resources or to become more conservative to

accommodate continued effects within the subbasins and the Basin.

Summary and Comparison

All of the alternatives lack specific performance

measures. Performance measures would be quantifiable ecological goals in the sense that they

measure a biological or physical process or state

(such as, water quality and instream RMOs); they

are not a measure of causal mechanisms. These

would be measures from which one could determine the desired future conditions of the stream,

watershed, or riparian vegetation. We do not view

these performance measures as absolute thresholds or targets, but rather in the sense of relative

health of the system, much like foresters view

measures of mortality, growth rate, and so on. If

the overall goal is to maintain and/or restore natural ecosystem processes and conditions, then

some performance measures are needed that can

be used to indicate if the current trend is moving

in the desired direction. For example, the science

literature supports that more ecological functions

Aquatics 449
and habitats along forest streams can be provided

if the adjacent stand is in a mature or late-successional condition (FEMAT 1993, Murphy 1995,

National Research Council 1995). Measures of

this condition are the number and size classes of

large trees for a given potential vegetation group

(PVG). If this condition exists or could be

attained, one could expect the instream conditions

to eventually reflect the desired instream conditions. Likewise, with limits on disturbance in

watersheds, the desired state could be maintained

or potentially restored in a shorter period of time

than if there were or had been no limits to watershed disturbance.

The instream RMOs are an attempt to quantitatively provide a measure of the current condition

of a stream or streambank. They reflect causal

mechanisms occurring recently or in the distant

past. Changes in these measurable instream characteristics could be a result of decades of past

degradation, a recent large flood, human disturbance, or multiple causes. In aggregate, RMOs are

useful in determining trends and current watershed conditions, but are not well connected to

planning and implementing ecosystem management within these alternatives.

Under Alternatives 2 through 6, RMO objectives

are not expected to be met instantaneously, but

rather would be achieved over time. While the

RMOs vary somewhat, the timeframe for attainment of RMOs does not appear to vary with

alternative except when concerning watershed

restoration activity levels. This reduces our ability

to use RMOs to evaluate their effectiveness within

each alternative. In Alternatives 4 and 6, "all of

the described features may not occur within a

watershed, but all generally should occur at the

watershed scale." We were given no guidance in

any alternative as to how the condition of a watershed relative to RMOs would affect project implementation. If RMOs are below standard for the

watershed, do projects continue that can further

degrade habitat? We assumed not. We further

assumed that if watershed analysis allowed one to

make changes in standards and guidelines in

Alternatives 3, 4, 6, and parts of Alternative 5,

such changes would not result in degradation or

halt restoration trends for habitats, populations,

or riparian conditions.

The alternatives are very complex and do not vary

systemically to allow a marginal evaluation of the

effectiveness of their components. We were often

required to evaluate them on the stated alternative

approach rather than on the specific elements of

an alternative. For example, the real difference

between Alternatives 4 and 6 is that they will be

implemented at different rates and that adaptive

management will figure more prominently in

Alternative 6. The difference between Alternatives

2 and 3 appears to be the immediate incorporation of new information gained through the science assessment.

In summary, five of seven alternatives articulated

an aquatic conservation strategy sufficient to

maintain and restore aquatic and riparian ecological processes through time (table 3.2), Alternative

7 gave the most direct and specific direction

regarding performance measures coupled with its

reserves and its passive approach. Alternative 6

with its emphasis on adaptive management and

cautious approach and Alternative 4 with its

aggressive restoration, had less-specific descriptions of processes and performance measures, but

RMAs were to be slope adjusted. Alternatives 2

and 3, with the ability to change widths of

RHCAs and RMOs with site-specific (not

watershed-specific) analysis, rated lower. Finally,

Alternatives 1 and 5 did not rate as ecologically

satisfactory in their ability to meet the goals

and objectives of the aquatic conservation

strategy.

450 Aquatics
Table 3.2. Suitability of proposed alternatives for aquatic ecosystem protection.

Evaluation Questions

Does the aquatic conservation strategy

maintain and restore aquatic and riparian ecological processes through time?

Is watershed or ecosystem analysis

required for specifically identified

watersheds?

Can standards and guidelines be

modified after ecosystem analysis?

What are the relative benefits of the

proposed intensity of riparian and

watershed restoration (road obliteration)?

Alternative

1

No

No, except

in FEMAT

1

key

watersheds

Highly

variable,

No

Low

2

Yes

Yes, but is

sitespecific,

not

ecosystemspecific

except in

FEMAT

1

key

watersheds

No

Moderate

3

Yes

Yes, but is

sitespecific,

not

ecosystemspecific

except in

FEMAT

1

key

watersheds

Yes

Moderate

4

Yes

Yes, watershed

analysis in

Category 1 and

all strongholds,

ecosystem

analysis in highpriority

watersheds and

FEMAT

1

 key

watersheds

Yes

High

5

Yes, in nonproduction

emphasis areas

No, in production

emphasis areas

Yes, ecosystem

analysis

in .Category 1 non

production

emphasis areas;

No, in production

emphasis areas

except FEMAT

1

key watersheds

Yes, in nonproduction

emphasis areas;

No, in production

emphasis areas

Moderate

I

I

o

'Forest Ecosystem Management Assessment Team (FEMAT). 1993. Forest ecosystem management: an ecological, economic, and social assessment. Portland, OR: U

Interior [and others], [irregular pagination].
Step 2: Projected Effects on

Widely-Distributed Salmonid

Species

The "Broadscale Assessment of Aquatic Species

and Habitats" (Lee and others, in press) identified

seven widely-distributed salmonids that serve as

indicators of environmental change. These seven

key salmonids are bull trout, westslope cutthroat

trout, Yellowstone cutthroat trout, redband trout,

steelhead, ocean-type chinook salmon, and

stream-type chinook salmon. In this exercise, we

identified the expected effect of the seven alternatives on future distribution and status of each of

these salmonids.

Major Assumptions and

Information Used to Judge

Alternatives

We followed the general assumptions identified by

the SIT for evaluating alternatives." Specific to

salmonids, we assumed that during implementation of the alternatives the presence or absence of

strong populations (strongholds), as defined by

the SIT in Lee and others (in press), would be

verified using local information when activity levels depended on such strongholds. For the purpose of our evaluation, however, we used known

and projected status maps (Lee and others, in

press) as a reasonable estimate of the current distribution and abundance of strongholds. In our

analysis we relied strongly on the information

regarding the distribution and status of fishes generated by the aquatic assessment (Lee and others,

in press). We also used the spatial and temporal

allocation of management activities and road densities developed in the preliminary draft EISs to

describe the patterns of management with the

potential to influence fishes under each of the

alternatives. We developed four primary pieces of

information as follows: (1) a series of classification

trees to describe current patterns in fish distribution associated with landscape characteristics and

to predict simple trends in distribution associated

with changes in those characteristics, (2) a summary of anticipated road density changes across

the current distribution of fishes, (3) a summary

of the current ownership and management cluster

for the current distribution of fishes, and (4) a

summary of the anticipated intensity of management activities across the current distribution of

fishes. Each informational piece provided some

sense of where and how much of the anticipated

management change was likely to influence each

of the species we considered. Each has important

limitations or inconsistencies and represents only

a single element in a larger and more complex picture. Any conclusions must be drawn from the

weight and consistency of trends anticipated from

the models, from the patterns in allocation of

roads and other land-disturbing activities, the

allocation of restoration activities, and the mitigation of disturbance expected through the standards and specific direction of the alternatives.

Classification trees—In order to help track

changes in population distribution and status that

might result from each alternative, we developed a

series of classification trees that linked population

status of each species to physical landscape features and management activities. We followed the

approach of Lee and others (in press), except that

we used a smaller subset of landscape variables to

describe the physical setting, and additional measures of road density that were calculated from the

one-square-kilometer (0.39 mi2) road-density data

summarized for each subwatershed [8,000-20,000

acre (3,239-8,097 ha) watersheds, 6th HUG]

(appendix 3-B). The resulting classification trees'

probability distributions associated with each

node are presented in appendix 3-B. Uncertainty

in classifications can be evaluated through classifi-

"Personal communication. March 15, 1996. Sylvia J. Arbelbide, Minerals Area Management Director, U.S. Forest Service, Pacific

Southwest Region, San Francisco, CA. Memo, on file with: U.S. Department of Agriculture, Forest Service, U.S. Department of

Interior, Bureau of Land Management, Interior Columbia Basin Ecosystem Management Project, 112 E. Poplar, Walla Walla,

WA 99362.

Aquatics
cation success tables (see Lee and others, in press).

However, because we used the existing patterns of

occurrence as estimates of the likelihood for a

given species occurrence under similar conditions

in the future, classification success is irrelevant.

Confidence intervals for the proportions could be

estimated but generally would be comparable in

magnitude to the estimated change in distribution. We did not conclude, therefore, that significant changes are likely or unlikely based only on

these simple models; we merely used them as an

indication of the trends that would be consistent

with changes in allocation of roads. The development and utility of classification trees with these

data are covered in detail in Lee and others (in

press).

The resultant classification trees consistently

showed that the likelihood of a strong population

decreased with increasing road density in many

portions of the landscape for all of the resident

species. We used classification trees to predict the

likelihood of strong populations and/or depressed

populations for each alternative, using the projected road densities in year 100. With the models,

we predicted a range of responses that were interpreted for each species by comparison with the

current condition. For example, Yellowstone cutthroat trout are currently classified as strong in

about 34 percent (Alternative 0 = 0.341 = 34%)

of the subwatersheds within the potential historical range (table 3.3). Under Alternative 1, the

probability assignment was 0.325 or a change of

-0.016 suggesting a declining trend in the occurrence of strong subwatersheds. The predicted loss

represents about 4.7 percent of the current distribution of strong subwatersheds across the assessment area. The results also suggest a negative but

less substantial change (0.9% of current) in the

combined distribution (strong and depressed) for

this subspecies (table 3.3).

From these results we could anticipate negative

trends in both the status and complete distribution of Yellowstone cutthroat trout associated with

the distribution of roads. We might further anticipate a larger change in status than in overall distribution. In other words, the changes from strong

to depressed are more likely to occur than are

changes from present to absent. Because the models were based on fish distributions and road density allocations by subwatershed, the predictions

could also be summarized by subbasin (table 3.4)

to provide a spatially explicit characterization of

the anticipated changes. In this example, larger

changes in status of subwatersheds should be

expected in the Salt subbasin than in the Teton

subbasin although both show a negative trend

(table 3.4). This information was summarized by

species and subbasin in a series of tables (tables

3.3-3.10) that were made available to the evaluation team.

The effects of increasing road densities include

more than simply the total number of roads; there

often are attendant landscape effects associated

with roads which cannot be directly measured or

projected (Lee and others, in press). Thus, we

used road density as a general indicator of human

disturbance. One could develop protracted arguments that future roads will not be as harmful as

historical roads, or alternatively, that removing

roads is not as favorable as having never built

them at all—all of which mases evaluating future

effects of roads problematic. To simplify, we

assumed that future distributions of fish would be

influenced by road-density patterns consistent

with current relationships unless clearly mitigated

by management. Therefore, the predicted changes

in probability assignments from the classification

trees are useful measures of relative changes that

are based on empirical patterns.

Whether or not projected roads and their related

effects will influence the status of fishes must be

drawn from these empirical patterns, an understanding of the limitations, and the likely mitigative or exacerbating effects of each alternative. It

is important to emphasize this point. Changes in

road densities projected from the preliminary

draft EIS may not reflect actual changes in roadrelated disturbance, but instead reflect the density of roads that are open and maintained.

Aquatics 453
Table 3.3. Projected changes in probability assignments for each alternative, Basin-wide and by species for

four resident salmonids.

Probability that species status is strong (STR), or either strong or depressed (SR).

Alternative

current*

1

2

3

4

5

6

7

Bull

STR

6.4%

5.9%

6.4%

6.5%

6.5%

6.3%

6.6%

6.7%

trout

SR

28.3%

26.8%

27.6%

27.9%

28.0%

27.6%

28.3%

29.1%

Westslope

STR

21 .4%

20.7%

21.1%

21 .7%

21.7%

21.1%

21.9%

22.4%

cutthroat

SR

75.8%

75.7%

75.8%

76.0%

76.0%

75.8%

76.0%

76.0%

Yellowstone

STR

34.1%

32.5%

34.1%

34.2%

34.5%

33.1%

34.5%

34.6%

cutthroat

SR

62.4%

61.9%

62.4%

62.4%

62.5%

61 .9%

62.5%

62.6%

Redband

STR

17.5%

17.1%

17.5%

17.5%

17.5%

17.4%

17.5%

17.5%

trout

SR

54.3%

54.3%

54.3%

54.3%

54.3%

54.3%

54.3%

54.3%

'Estimates for current condition.

Relative change* in STR and SR between current and each alternative (DSTR and DSR, respectively).

Alternative

Bull trout

DSTR DSR

Westslope cutthroat

DSTR DSR

Yellowstone cutthroat

DSTR DSR

Redband trout

DSTR DSR

1

2

3

4

5

6

7

-8.5%

-0.8%

1 .8%

2.1%

-2.0%

2.8%

4.3%

-5.2%

-2.3%

-1 .3%

-1.1%

-2.4%

-0.1%

2.9%

-3.4%

-1.6%

1.2%

1.2%

-1.4%

2.4%

4.4%

-0.2%

0.0%

0.2%

0.2%

0.0%

0.2%

0.3%

-4.8%

—

0.2%

1 .2%

-3.1%

1 .0%

1.4%

-0.9%

—

0.0%

0.2%

-0.8%

0.2%

0.3%

-2.0%

-0.1%

0.1%

0.2%

-0.7%

0.2%

0.2%

—

—

—

—

—

—

"Relative change is calculated as [(projected - current) / current].

Thus, reductions in projected road density may

only equate to road closures and not necessarily to

road obliteration. Reductions in road density projected through the preliminary draft EISs may not

carry the full ecologic and hydrologic benefits associated with true road obliteration, while at the

same time increases in density may still carry the

full costs. The analysis must be based on trends

and a more subjective interpretation of the likely

mitigation or exacerbation of that trend as it is tied

to watershed restoration activities (for example,

true road obliteration and the associated standards

under each alternative). Trends predicted with

models also are not dramatic and may be understated. For example, relationships between current

road densities and the distribution and status of

anadromous fishes are weak. This does not imply

that roads and their related effects are not important for anadromous fish habitats, rather that the

effects of roads may be confounded by the resolution of available data, the limited sample size, and

other causes of decline (Lee and others, in press).

Other factors likely to influence fish populations

are included only to the degree that they will be

represented by roads as a surrogate measure of that

disturbance.

454 Aquatics
Table 3.4. Projected changes in probability assignments for Alternative 1, by species.

Alternative 1

EIS Subbasin

EEIS Methow

Upper Columbia-Entiat

Wenatchee

Naches

Upper Malheur

Brownlee Reservoir

Imnaha

Upper John Day

North Fork John Day

Middle Fork John Day

Upper Klamath Lake

UCRB Upper Kootenai

Fisher

Yaak

Lower Kootenai

Moyie

Upper Clark Fork

Flint-Rock

Blackfoot

Middle Clark Fork

Bitterroot

Stillwater

Swan

Lower Clark Fork

Priest

St. Joe

Palisades

Salt

Teton

Big Lost

Big Wood

North & Middle Fork Boise

Boise-Mores

South Fork Boise

South Fork Payette

Middle Fork Payette

Payette

North Fork Payette

Weiser

Pahsimeroi

Middle Salmon-Panther

Lemhi

Middle Salmon-Chamberlain

South Fork Salmon

Lower Salmon

Little Salmon

Upper Selway

Lochsa

South Fork Clearwater

Upper N. Fork Clearwater

Lower N. Fork Clearwater

Bull

Trout

DSTR* DSR*

-1.1%

-1.1%

-0.4%

0.3%

-0.2%

-1.6%

-0.1%

-0.2%

-0.5%

-0.4%

-0.2%

-0.4%

-0.3%

0.1%

-3.1%

-0.7%

-0.3%

-1 .2%

-0.5%

-1 .3%

-0.3%

-0.1%

-0.2%

—

—

—

-8.0%

-3.9%

-1.2%

-8.6%

-0.6%

-1.4%

-0.1%

-0.5%

-0.1%

-1 .6%

-1 .7%

-1 .0%

-0.5%

-4.0%

-0.6%

-2.3%

-0.1%

-0.1%

-0.2%

-0.4%

-0.2%

-4.5%

-4.5%

-1 .5%

-2.1%

-2.6%

—

-0.9%

-2.8%

-5.1%

-4.0%

-1 .4%

-2.2%

-2.4%

2.3%

-7.0%

-3.0%

-2.8%

-9.4%

-5.9%

-15.2%

-3.1%

-1.0%

-2.3%

—

—

—

-0.2%

—

-4.7%

-0.7%

-16.3%

-1 .2%

-5.0%

-0.8%

—

-2.7%

-0.3%

-1 .2%

-3.3%

-6.9%

-10.6%

-1 .5%

-0.9%

-2.3%

-4.1%

-2.0%

Westslope Yellowstone Redband

Cutthroat Cutthroat Trout

DSTR DSR DSTR DSR DSTR DSR

-0.6%

0.6%

—

—

—

-1.1%

—

-3.1%

-1.9%

-1.1%

-7.9%

-2.7%

-0.5%

0.0%

—

-3.0%

-1 .0%

—

-0.5%

—

—

—

—

—

—

—

-7.6%

-0.6%

-0.7%

-1.3%

-0.8%

—

—

—

—

-6.4%

-0.3% —

0.4% —

— —

— —

— —

-0.1% —

— —

-0.3% —

-0.4% —

-1 .4% —

-3.0% —

-0.1% —

-0.1% —

-0.6% —

— —

0.0% —

0.0% —

— —

-0.1% —

— -8.8%

— -16.5%

— -2.9%

— —

— —

— —

— —

1.1% —

0.2% —

-0.1% —

-1.1% —

0.0% —

— —

— —

— —

— —

0.1% —

— —

— -0.6%

— —

— -1 .3%

— —

— -3.7%

— —

— —

— —

— —

— —

— —

— —

— —

— —

— —

— —

-1.0% —

-9.1% —

-0.2% —

— -3.8%

— -6.0%

— -8.0%

— -2.8%

— -1 1 .3%

— -6.7%

— -2.3%

— -0.9%

— —

— —

— -1.2%

— —

— —

— —

— —

— —

— —

— -0.6%

—

0.0%

—

0.0%

—

0.1%

—

—

—

—

—

—

—

—

—

—

—

—

—

—

0.1%

0.2%

0.3%

0.1%

0.4%

0.2%

0.1%

0.0%

—

—

0.0%

—

—

—

—

—

—

0.0%

*DSTR = Change in the probability that species status is strong; DSR = Change in the probability that species status is depressed or strong.

"Change" is the difference between the alternative and current.

Aquatics 485
Table 3.5. Projected changes in probability assignments for Alternative 2, by species.

Alternative 2

EIS Subbasin

EEIS Upper Columbia-Entiat

Burnt

Powder

Upper Grande Ronde

Upper John Day

North Fork John Day

Middle Fork John Day

Williamson

Upper Klamath Lake

UCRB Upper Kootenai

Fisher

Yaak

Lower Kootenai

Moyie

Blackfoot

Middle Clark Fork

Bitterroot

Stillwater

Swan

Lower Clark Fork

Priest

St. Joe

Boise-Mores

Lower Salmon

Little Salmon

South Fork Clearwater

Upper N. Fork Clearwater

Lower N. Fork Clearwater

Bull

Trout

DSTR* DSR*

-1.1%

1 .3%

0.6%

0.9%

0.5%

2.8%

1.1%

-0.3%

-0.2%

-0.4%

-0.3%

-0.7%

-0.3%

-0.8%

-0.5%

-1.0%

-0.3%

-0.1%

-0.2%

0.3%

-0.3%

-1.8%

-0.2%

-0.4%

-0.2%

-4.5%

6.8%

1 .9%

4.9%

2.4%

2.8%

3.4%

-3.1%

-1 .4%

-2.2%

-2.4%

-2.5%

-2.8%

-6.0%

-5.9%

-1 1 .9%

-3.1%

-1 .0%

-2.3%

2.4%

-2.9%

-5.3%

-2.3%

-4.1%

-2.0%

Westslope

Cutthroat

DSTR DSR

—

—

—

-0.7%

—

-3.1%

-1.9%

-2.3%

-0.5%

-0.1%

—

-3.0%

-0.7%

—

-0.5%

—

—

—

—

-6.4%

—

—

—

-0.1%

—

-0.3%

-0.4%

0.0%

-0.1%

-0.5%

—

0.0%

-0.1%

—

-0.1%

—

—

—

—

0.1%

Yellowstone Redband

Cutthroat Trout

DSTR DSR DSTR DSR

— — — —

— — — —

— — 1.1% 0.0%

— — -3.7% 0.1%

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — -0.6% 0.0%

*DSTR = Change in the probability that species status is strong; DSR = Change in the probability that species status is depressed or strong.

"Change" is between the alternative and current.

Road distributions—To examine potential patterns of road disturbance on aquatic habitats independent of the models, we also cross-tabulated current known status with current and projected roaddensity class for each species of interest (table

3.11). Interpretation of these tables was based on a

comparison of distributions of road-density class

with each alternative. For example, 46 subwatersheds supporting strong Yellowstone cutthroat populations are presently classified as "none" in mean

road density (table 3.11). No change is projected

for the number of currently strong watersheds in

this road-density class under Alternative 1. Some

decline in the number of subwatersheds classified

as "very low" or "low" is projected while an

increase in the number classified as "moderate" or

"high" is also expected. The projected trend, then,

is for an increase in road densities associated with

watersheds currently supporting strong Yellowstone

cutthroat trout. As discussed in the previous section, interpretations tied to road densities must be

tempered by the understanding that projected

reductions in road densities under each alternative

do not necessarily equate to true road obliteration.

Changes in road densities provide only trend information that may understate associated negative

hydrologic and ecologic effects. Road-density

changes must therefore be interpreted as trends and

in light of the mitigating effects of each alternative.

48S Aquatics
Table 3.6. Projected changes in probability assignments for Alternative 3, by species.

Alternative 3

EIS Subbasin

EEIS Pend Oreille

Kettle

Sanpoll

Methow

Upper Columbia-Entiat

Wenatchee

Naches

Burnt

Powder

Imnaha

Upper Grande Ronde

Wallowa

North Fork John Day

Middle Fork John Day

Upper Deschutes

Williamson

Upper Klamath Lake

UCRB Upper Kootenai

Fisher

Yaak

Lower Kootenai

Moyie

Upper Clark Fork

Flint-Rock

Blackfoot

Middle Clark Fork

Bitterroot

Stillwater

Swan

Lower Clark Fork

Pend Oreille Lake

Priest

Upper Coeur D.alene

St. Joe

Palisades

North & Middle Fork Boise

Boise-Mores

South Fork Payette

Middle Salmon-Chamberlain

Lower Salmon

Little Salmon

Lower Selway

Lochsa

South Fork Clearwater

Clearwater

Upper N. Fork Clearwater

Lower N. Fork Clearwater

Bull

Trout

DSTR* DSR*

0.3%

0.5%

0.5%

0.8%

-1.1%

0.4%

-0.4%

1 .3%

0.6%

0.1%

0.9%

0.2%

2.0%

0.4%

2.9%

—

—

0.6%

0.3%

0.3%

0.1%

0.3%

0.1%

-0.1%

-0.4%

0.2%

—

0.1%

-0.5%

-0.1%

0.1%

0.7%

0.9%

-0.1%

—

0.2%

-1 .2%

0.1%

0.1%

0.0%

-1.0%

0.1%

0.3%

0.7%

0.1%

-0.1%

0.1%

0.9%

1.0%

1 .4%

2.1%

-4.5%

—

—

6.8%

1 .9%

1 .6%

4.9%

2.1%

—

-5.1%

—

—

—

-2.3%

-1.4%

-2.2%

0.3%

—

2.2%

-0.6%

-0.9%

-2.8%

-4.4%

-4.8%

-8.6%

-3.1%

0.9%

2.6%

—

-2.1%

—

0.6%

—

0.4%

1.3%

-1.9%

-2.6%

0.2%

-0.6%

-0.8%

—

-4.0%

-2.0%

Westslope

Cutthroat

DSTR DSR

2.6%

—

—

3.4%

4.1%

1 .6%

1 .7%

—

—

—

—

—

—

—

—

—

—

1.0%

—

—

-3.1%

-1.9%

-1.1%

2.6%

-2.3%

—

-0.7%

—

-3.0%

0.1%

—

1.1%

—

-0.5%

—

—

—

—

0.7%

—

—

1 .4%

2.5%

—

2.8%

-5.0%

—

0.0%

—

—

1 .6%

2.1%

0.2%

0.9%

—

—

—

—

—

—

—

—

—

—

-0.3%

—

—

-0.3%

-0.4%

-1 .4%

0.0%

0.0%

—

-0.1%

—

0.0%

-0.2%

—

-0.2%

—

-0.1%

—

—

—

—

0.2%

—

—

0.7%

1 .3%

—

1.4%

0.1%

—

Yellowstone Redband

Cutthroat Trout

DSTR DSR DSTR DSR

— — —

— — —

— — —

— — —

— — —

— — —

— — —

— — —

— — —

— — —

— — —

— — —

_ _ _

— — —

— — 0.5%

— — 1.1%

— — 1.9%

— — —

— — —

— — —

— — —

— — —

— — —

— — —

— — —

— — —

— — —

— — —

— — —

— — —

— — —

— — —

— — —

— — —

1 .2% 0.4% —

— — 1.0%

— — -2.8%

— — 1.1%

— — —

— — —

— — —

— — —

— — —

— — —

— — —

— — -0.6%

— — —

—

—

—

—

—

—

—

—

—

—

—

—

—

—

0.0%

0.0%

-0.1%

—

—

—

—

—

—

—

—

—

—

—

—

—

—

—

—

—

—

0.0%

0.1%

0.0%

—

—

—

—

—

—

—

0.0%

—

* DSTR = Change in the probability that species status is strong; DSR

"Change" is between the alternative and current.

Change in the probability that species status is depressed or strong.

Aquatics 45?
Table 3.7. Projected changes in probability assignments for Alternative 4, by species.

Alternative 4

EIS Subbasin

EEIS Pend Oreille

Kettle

Sanpoil

Okanogan

Methow

Upper Columbia-Entiat

Wenatchee

Naches

Brownlee Reservoir

Burnt

Powder

Imnaha

Upper Grande Ronde

Wallowa

Upper John Day

North Fork John Day

Middle Fork John Day

Upper Deschutes

Lower Crooked

Williamson

Upper Klamath Lake

UCRB Upper Kootenai

Fisher

Yaak

Lower Kootenai

Moyie

Upper Clark Fork

Flint-Rock

Blackfoot

Middle Clark Fork

Bitterroot

Stillwater

Swan

Lower Clark Fork

Pend Oreille Lake

Priest

Upper Coeur D.alene

St. Joe

Palisades

Salt

Lower Henrys

Portneuf

North & Middle Fork Boise

Boise-Mores

South Fork Payette

Middle Fork Payette

North Fork Payette

Weiser

Middle Salmon-Chamberlain

Lower Salmon

Little Salmon

Lower Selway

Lochsa

South Fork Clearwater

Bull

Trout

DSTR* DSR*

0.3%

0.5%

0.5%

0.0%

0.8%

-1.1%

0.4%

-0.4%

0.3%

1.3%

0.6%

0.1%

0.9%

0.2%

0.3%

2.0%

0.4%

3.1%

0.6%

0.3%

0.3%

0.1%

0.3%

0.1%

-0.1%

-0.5%

0.2%

0.1%

-0.5%

-0.1%

0.1%

0.7%

0.9%

-0.1%

0.2%

-1.2%

0.1%

0.9%

0.3%

0.3%

0.1%

0.0%

-1.0%

0.1%

0.3%

0.7%

0.9%

1 .0%

1.4%

2.1%

-4.5%

2.3%

6.8%

1 .9%

1 .6%

4.9%

2.1%

0.5%

-5.1%

-2.3%

-1.4%

-2.2%

0.3%

2.2%

-0.6%

-1.4%

-2.8%

-4.4%

-4.8%

-8.6%

-3.1%

0.9%

2.6%

-2.1%

0.6%

—

0.4%

4.0%

1 .6%

2.4%

1.3%

-1.9%

-2.6%

0.2%

-0.6%

-0.8%

Westslope

Cutthroat

DSTR DSR

2.6%

3.4%

4.1%

1.6%

1 .7%

1.0%

-3.1%

-1.9%

-1.1%

2.6%

-1.9%

-0.7%

-3.0%

0.1%

1.1%

-0.5%

—

—

—

—

—

0.7%

—

—

1.4%

2.5%

—

0.0%

1.6%

2.1%

0.2%

0.9%

-0.3%

-0.3%

-0.4%

-1 .4%

0.0%

0.0%

-0.1%

0.0%

-0.2%

-0.2%

-0.1%

—

—

—

—

—

0.2%

—

—

0.7%

1.3%

—

Yellowstone Redband

Cutthroat Trout

DSTR DSR DSTR DSR

— — 0.5%

— — 0.8%

— — 1.1%

— — 1 .9%

1.2% 0.4% —

0.9% 0.1% —

3.4% 2.4% —

1.8% 0.1% —

— — 1.0%

— — -2.8%

— — 1.1%

— — 2.3%

— — 1.7%

— — —

— — —

— — —

— — —

— — —

— — —

— — —

-20.0%

-30.0%

-40.0%

-60.0%

0.0%

0.1%

0.0%

-0.1%

-0.1%

—

—

—

—

—

—

—

458 Aquatics
Table 3.7 (continued)

Bull Westslope Yellowstone Redband

Alternative 1 Trout Cutthroat Cutthroat Trout

EIS Subbasin DSTR* DSR* DSTR DSR DSTR DSR DSTR DSR

Clearwater

Upper N.

Lower N.

Fork

Fork

Clearwater

Clearwater

0.

-0,

0

.1%

.1%

.1%

-4.0%

-2.0%

2.8%

-5.0%

—

1.

0.

.4%

.1%

—

— — -0,

— —

,6%

—

0.0%

—

*DSTR = Change in the probability that species status is strong; DSR = Change in the probability that species status is depressed or strong.

"Change" is between the alternative and current.

Table 3.8. Projected changes in probability assignments for Alternative 5, by species.

Alternative 5

EIS Subbasin

EEIS Upper Columbia-Entiat

Brownlee Reservoir

Burnt

Powder

Upper Grande Ronde

Upper John Day

North Fork John Day

Middle Fork John Day

Williamson

Upper Klamath Lake

UCRB Upper Kootenai

Fisher

Yaak

Lower Kootenai

Moyie

Upper Clark Fork

Blackfoot

Middle Clark Fork

Bitterroot

Stillwater

Swan

Lower Clark Fork

Priest

St. Joe

Salt

Teton

Big Lost

Big Wood

Boise-Mores

Middle Fork Payette

Payette

North Fork Payette

Weiser

Lower Salmon

Little Salmon

South Fork Clearwater

Clearwater

Upper N. Fork Clearwater

Lower N. Fork Clearwater

Bull

Trout

DSTR* DSR*

-1.1%

1.3%

0.6%

0.9%

0.3%

2.0%

0.4%

-0.4%

-0.2%

-0.4%

-0.3%

0.1%

-0.4%

-0.3%

—

-0.5%

-0.5%

-0.3%

-0.1%

-0.2%

—

—

-8.0%

-1 .2%

-1 .4%

-0.1%

-0.5%

-0.1%

0.0%

-1 .0%

0.7%

0.1%

-0.4%

-0.2%

-4.5%

6.8%

1 .9%

4.9%

0.5%

-5.1%

-4.0%

-1.4%

-2.2%

-2.4%

2.2%

-0.9%

-2.8%

-4.4%

-5.9%

-8.6%

-3.1%

-1 .0%

-2.3%

—

—

—

-16.3%

-1.2%

-5.0%

-0.8%

-1.9%

-2.6%

-0.8%

—

-4.1%

-2.0%

Westslope Yellowstone

Cutthroat Cutthroat

DSTR DSR DSTR DSR

—

—

—

—

-1.1%

—

-3.1%

-1.9%

-1.1%

-2.3%

-0.5%

-0.7%

—

-3.0%

-1.0%

—

-0.5%

—

—

—

—

—

—

—

2.8%

-6.4%

— — —

— — —

— — - —

— — —

-0.1% — —

— — —

-0.3% — —

-0.4% — —

-1.4% — —

0.0% — —

-0.1% — —

-0.1% — —

— — —

0.0% — —

0.0% — —

— — —

-0.1% — —

— -16.5% -9.1%

— -2.9% -0.2%

— — —

— — —

— — —

— — —

— — —

1 .4% — —

0.1% — —

Redband

Trout

DSTR DSR

-1 .3%

—

—

1.1%

1 .9%

—

—

—

—

—

—

—

—

—

—

—

—

-3.8%

-6.0%

-2.8%

-2.3%

-0.9%

—

—

—

—

-0.6%

0.0%

—

—

0.0%

-0.1%

—

—

—

—

—

—

—

—

—

—

—

—

0.1%

0.2%

0.1%

0.1%

0.0%

—

—

—

—

0.0%

*DSTR = Change in the probability that species status is strong; DSR = Change in the probability that species status is depressed or strong.

"Change" is the difference between the alternative and current.

Aquatics
Table 3.9. Projected changes in probability assignments for Alternative 6, by species.

Alternative 6

EIS Subbasin

EEIS Pend Oreille

Kettle

Sanpoil

Methow

Upper Columbia-Entiat

Wenatchee

Naches

Burnt

Powder

Imnaha

Upper Grande Ronde

Wallowa

Upper John Day

North Fork John Day

Middle Fork John Day

Upper Deschutes

Williamson

Upper Klamath Lake

UCRB Upper Kootenai

Fisher

Yaak

Lower Kootenai

Moyie

Flint-Rock

Blackfoot

Middle Clark Fork

Stillwater

Swan

Lower Clark Fork

Pend Oreille Lake

Priest

Upper Coeur D.alene

St. Joe

Palisades

Lower Henrys

Portneuf

North & Middle Fork Boise

Boise-Mores

South Fork Payette

Middle Salmon-Chamberlain

Little Salmon

Lower Selway

Lochsa

South Fork Clearwater

Clearwater

Upper N. Fork Clearwater

Lower N. Fork Clearwater

Bull

Trout

DSTR* DSR*

0.3%

0.5%

0.5%

0.8%

-1.1%

0.4%

-0.4%

1.3%

0.6%

0.1%

0.9%

0.2%

0.5%

2.8%

1.1%

2.9%

—

—

0.6%

0.3%

0.3%

0.1%

0.3%

-0.1%

0.2%

0.2%

0.1%

0.2%

-0.1%

0.1%

0.7%

0.9%

-0.1%

—

—

—

0.2%

0.3%

0.1%

0.1%

0.6%

0.1%

0.3%

0.9%

0.1%

-0.1%

0.1%

0.9%

1 .0%

1 .4%

2.1%

-4.5%

—

—

6.8%

1 .9%

1 .6%

4.9%

2.1%

2.4%

2.8%

3.4%

—

—

—

-2.3%

-1 .4%

-2.2%

0.3%

0.0%

-0.6%

1.3%

-2.8%

-4.8%

-0.4%

-3.1%

0.9%

2.6%

—

-2.1%

—

—

—

0.6%

2.4%

0.4%

1 .3%

5.6%

0.2%

-0.6%

1 .6%

—

-4.0%

-2.0%

Westslope

Cutthroat

DSTR DSR

2.6%

—

—

3.4%

4.1%

1 .6%

1 .7%

—

—

—

—

—

—

—

—

—

—

—

1 .0%

—

—

-3.1%

-1.9%

2.6%

1.6%

—

—

1.1%

0.1%

—

1.1%

—

-0.5%

—

—

—

—

—

—

0.7%

—

1.4%

2.5%

—

2.8%

-5.0%

—

0.0%

—

—

1 .6%

2.1%

0.2%

0.9%

—

—

—

—

—

—

—

—

—

—

—

-0.3%

—

—

-0.3%

-0.4%

0.0%

-0.1%

—

—

0.1%

-0.2%

—

-0.2%

—

-0.1%

—

—

—

—

—

—

0.2%

—

0.7%

1.3%

—

1 .4%

0.1%

—

Yellowstone Redband

Cutthroat Trout

DSTR DSR DSTR DSR

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — 0.5% 0.0%

— — 1.1% 0.0%

— — 1.9% -0.1%

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

1.2% 0.4% — —

3.4% 2.4% — —

1.8% 0.1% — —

— — 1.0% 0.0%

— — — —

— — 1.1% 0.0%

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — -0.6% 0.0%

— — — —

*DSTR = Change in the probability that species status is strong; DSR = Change in the probability that species status is depressed or strong.

"Change" is the difference between the alternative and current.

46D Aquatics
Table 3.10. Projected changes in probability assignments for Alternative 7, by species.

Alternative 7

EIS Subbasin

EEIS Pend Oreille

Kettle

Sanpoil

Methow

Upper Columbia-Entiat

Wenatchee

Naches

Burnt

Powder

Imnaha

Upper Grande Ronde

Wallowa

Upper John Day

North Fork John Day

Middle Fork John Day

Upper Deschutes

Williamson

Upper Klamath Lake

UCRB Upper Kootenai

Fisher

Yaak

Lower Kootenai

Moyie

Flint-Rock

Blackfoot

Middle Clark Fork

Flathead Lake

Stillwater

Swan

Lower Clark Fork

Pend Oreille Lake

Priest

Upper Coeur D'Alene

St. Joe

Palisades

Upper Henrys

Lower Henrys

Portneuf

North & Middle Fork Boise

Boise-Mores

South Fork Payette

North Fork Payette

Middle Salmon-Chamberlain

Little Salmon

Lower Selway

Lochsa

South Fork Clearwater

Clearwater

Upper N. Fork Clearwater

Lower N. Fork Clearwater

Bull

Trout

DSTR* DSR*

0.3%

0.7%

0.5%

0.8%

0.4%

-0.4%

1 .3%

0.6%

0.1%

0.9%

0.2%

0.5%

2.8%

1.1%

3.1%

1.1%

0.7%

1 .5%

0.6%

1 .3%

-0.1%

0.2%

0.7%

0.5%

1 .0%

0.2%

0.9%

0.4%

0.7%

1.1%

0.2%

—

—

0.2%

0.3%

0.1%

0.1%

0.1%

0.6%

0.1%

0.3%

0.9%

0.1%

0.3%

0.3%

0.9%

3.5%

1 .4%

2.1%

6.8%

1 .9%

1.6%

4.9%

2.1%

2.4%

2.8%

3.4%

3.9%

2.9%

13.5%

6.1%

1 1 .9%

-0.6%

1 .3%

2.1%

1 .4%

5.6%

-0.4%

2.0%

4.6%

2.6%

2.0%

0.8%

—

—

0.6%

2.4%

0.4%

1 .4%

1 .3%

5.6%

0.2%

-0.6%

1 .6%

—

1 .2%

1 .0%

Westslope

Cutthroat

DSTR DSR

2.6%

3.4%

4.1%

1 .6%

1 .7%

—

—

3.7%

1 .0%

0.7%

3.5%

2.6%

2.0%

1.1%

—

—

1.1%

1 .8%

—

2.2%

—

—

—

—

—

0.7%

—

1 .4%

2.5%

—

2.8%

0.8%

0.0%

1 .6%

2.1%

0.2%

0.9%

—

—

-0.2%

0.1%

0.2%

-0.3%

0.0%

-0.1%

0.0%

—

—

0.1%

0.0%

—

-0.3%

—

—

—

—

—

0.2%

—

0.7%

1.3%

—

1 .4%

-0.1%

Yellowstone Redband

Cutthroat Trout

DSTR DSR DSTR DSR

— — — —

— — — —

— — 0.5% 0.0%

— — 1.1% 0.0%

— — 1.9% -0.1%

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

— — — —

1.2% 0.4% — —

2.4% 0.6% — —

3.4% 2.4% — —

1.8% 0.1% — —

— — 1 .0% 0.0%

— — — —

— — 1.1% 0.0%

— — — —

— — — —

— — — —

— — — —

__ __ __

*DSTR = Change in the probability that species status is stron:

"Change" is the difference between the alternative and current.

ig; DSR = Change in the probability that species status is depressed or strong.

Aquatics 461
Table 3.11. Current known status (strong or depressed) for each of seven salmonids versus current (Alternative 0) mean road density class and the projected allocation and distribution of road density classes for

each alternative.

Bull trout

Alternative

0

1

2

3

4

5

6

7

Mean Road Density (miles of road

Status

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

None

<0.02

60

124

54

117

59

123

59

121

59

121

59

121

60

124

60

124

Very Low

0.02 - 0.1

24

24

20

19

25

26

29

33

30

33

27

28

29

30

31

30

Low

0.1 - 0.7

134

72

112

72

137

66

188

70

192

71

141

67

205

74

221

76

Moderate

0.7- 1.7

238

22

241

32

256

27

403

38

403

37

301

29

387

34

370

32

/mi2)

Extremely

High High

1.7-4.7 >4.7

352

28

381

30

333

28

133

8

128

8

283

25

131

8

130

8

4

0

4

0

2

0

0

0

0

0

1

0

0

0

0

0

Westslope cutthroat trout

Alternative Status

0

1

2

3

4

5

6

7

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Mean Road Density (miles of road

None

<0.02

87

192

79

185

81

191

81

191

81

191

81

191

87

191

87

192

Very Low

0.02 - 0.1

39

34

35

31

42

34

47

40

47

40

44

35

44

41

45

40

Low

0.1 - 0.7

180

109

151

98

174

102

210

136

210

136

174

105

228

140

237

154

Moderate

0.7-1.7

350

110

348

117

342

115

788

194

794

195

430

129

775

189

769

175

/mi2)

Extremely

High High

1.7-4.7 >4.7

822

139

865

153

839

142

358

24

352

23

750

125

350

24

346

24

7

3

7

3

7

3

1

2

1

2

6

2

1

2

1

2

Aquatics
Table 3.11 (continued)

Yellowstone cutthroat trout

Alternative

0

1

2

3

4

5

6

7

Redband trout

Alternative

0

1

2

3

4

5

6

7

Status

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Status

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

None

<0.02

4

46

2

46

4

46

4

46

4

46

4.

46

4

46

4

46

None

<0.02

148

49

135

34

148

49

148

47

148

48

141

38

148

49

148

49

Mean Road

Very Low

0.02 - 0.1 0

8

25

2

21

8

25

8

25

8

25

7

25

8

25

8

25

Mean Road

Very Low

0.02 - 0.1 0

37

24

32

20

37

25

38

36

40

38

39

26

39

36

40

37

Density

Low

.1 -0.7

19

59

20

56

19

59

20

59

28

60

17

55

23

59

23

59

Density

Low

.1 -0.7

365

114

339

115

360

118

406

121

416

129

364

127

417

128

425

127

(miles of road

Moderate

0.7- 1.7

51

42

51

45

50

42

52

43

49

42

47

45

51

43

51

43

(miles of road

Moderate

0.7- 1.7

678

188

702

200

829

282

973

343

1025

370

911

312

987

340

982

340

/mi2)

High

1.7-4.7

91

37

98

41

92

37

89

36

84

36

98

38

87

36

87

36

/mi2)

High

1.7-4.7

772

428

792

434

637

339

451

266

388

228

557

310

425

260

422

260

Extremely

High

>4.7

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

Extremely

High

>4.7

21

13

21

13

10

3

5

3

4

3

9

3

5

3

4

3

Aquatics 463
Table 3.11 (continued)

Steelhead trout

Alternative

0

1

2

3

4

5

6

7

Status

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Stream-type chinook salmon

Alternative

0

1

2

3

4

5

6

7

Status

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

None

<0.02

199

0

189

0

199

0

197

0

197

0

197

0

199

0

199

0

None

<0.02

101

0

97

0

101

0

100

0

100

0

100

0

101

0

101

0

Mean

Very Low

0.02 - 0.1

52

0

45

0

53

0

63

0

63

0

57

0

61

0

61

0

Mean

Very Low

0.02 - 0.1

30

2

31

2

31

2

34

2

34

2

32

2

33

2

33

2

Road Density

Low

0.1 - 0.7

240

3

224

2

242

5

281

4

281

4

241

4

289

5

290

5

Road Density

Low

0.1 -0.7

129

1

110

1

131

2

161

2

161

2

131

2

167

2

168

2

(miles of road

Moderate

0.7-1.7

406

7

423

7

490

13

629

16

635

16

583

14

628

15

628

15

(miles of road

Moderate

0.7-1.7

153

1

164

1

193

3

275

3

276

3

248

3

270

3

270

3

/mi2)

High

1.7-4.7

518

12

534

13

443

5

258

3

252

3

350

5

251

3

250

3

/mi2)

High

1.7-4.7

247

3

258

3

210

1

97

1

96

1

156

1

96

1

95

1

Extremely

High

>4.7

16

1

16

1

4

0

3

0

3

0

3

0

3

0

3

0

"

Extremely

High

>4.7

8

1

8

1

2

0

1

0

1

0

1

0

1

0

1

0

Aquatics
Table 3.11 (continued)

Ocean-type

Alternative

0

1

2

3

4

5

6

7

chinook salmon

Status

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Depressed

Strong

Mean Road Density (miles of road /

None

<0.02

4

0

3

0

4

0

4

0

4

0

4

0

4

0

4

0

Very Low

0.02 - 0.1

1

0

2

0

1

0

2

0

2

0

1

0

2

0

2

0

Low

0.1 -0.7

15

7

15

7

15

7

15

7

15

7

15

7

15

7

15

7

Moderate

0.7-1.7

30

12

30

12

30

12

43

15

44

15

30

12

43

15

43

15

'mi2)

Extremely

High High

1.7-4.7 >4.7

21

6

21

6

21

6

7

3

6

3

21

6

7

3

7

3

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

Ownership and management class—We crosstabulated the current known and predicted status

of each key species with an ownership and management designation developed by the SIT Aquatics

Team (Lee and others, in press) for each subwatershed (tables 3.12-3.18). Allocation of ownership

and management designation was used to consider

the relative significance of management activities

on FS- and BLM-administered lands. For example,

139 subwatersheds known or predicted to support

strong Yellowstone cutthroat trout are found on

Forest Service-administered lands (for example,

management clusters: FG, FH, FM, FW in table

3.14) but none are on BLM-administered lands

(management cluster BR in table 3.14). Thus, approximately 66 percent of all the currendy strong

populations are associated with FS-administered

lands and are likely to be influenced directly by the

activities considered under these alternatives.

Management activities—The projected forest

and range management activities vary in intensity

under each alternative. They also vary spatially

within and among the alternatives by forest and

rangeland cluster. To further our evaluation of the

potential influence of management activities on

the distribution and status of the salmonid

species, we summarized activities across species

distributions and status classifications. We considered timber harvest, thinning, watershed restoration, prescribed burning, livestock management,

and riparian restoration as potentially important

management activities in our summary. All activities were not given equal importance. For example, livestock management is expected to have

only a minor influence on aquatic habitats relative

to active riparian restoration, which includes fencing and the potential to fully exclude livestock

from critical habitats.

Management activities summary tables were generated in a four-step process. First, we tallied the

number of subwatersheds for each species and

status-class by forest and rangeland clusters and

summarized as a proportion of the total occurrence in the entire assessment area (table 3.19).

For example, 62 percent of the Yellowstone cutthroat trout subwatersheds currently considered

strong occur in Forest Cluster 1 (table 3.19).

Second, we used the assignment of activity levels

and the midpoint of reported rates for each activity (see appendix I; tables 3 and 10 in the "Rule

Sets for Management Activity Levels by Cluster by

Alternative" section of the preliminary draft EIS)

Aquatics 46$
to estimate the rate of implementation for each

activity by cluster and alternative. Third, we multiplied the activity rate by the proportion of the

species distribution occurring in the appropriate

forest or range cluster. Finally, we summed across

cluster by species occurrence, status, or class to

estimate the total proportion of the distribution

that would be influenced by a particular activity

per decade (table 3.20). For example, under

Alternative 1 we would anticipate that 2.8 percent

of the current distribution of strong subwatersheds for Yellowstone cutthroat trout would be

exposed to timber harvest per decade, 1.3 percent

to thinning, 1.3 percent to watershed restoration

(table 3.20), and so on.

We assumed that an activity would have the same

effect in any watershed unless mitigating or exacerbating activities were clearly identified within

the alternative. The summaries provided simple

indices for comparisons across species distributions and among alternatives. Many land-use

management activities have been generally associated with disruption of watershed function and

negative effects on the processes that maintain and

create high-quality habitats for fishes (Lee and

others, in press). However, we had no method to

weigh or model the effects of land use and management activities allocated under each alternative

as we did with road allocation. Thus, we were

forced to evaluate risks largely on the content and

direction of each alternative and the allocation of

activities across a species range.

Although the risks associated with land use can be

mitigated by careful planning, analysis, and implementation, we generally assumed that increased

levels of ground-disturbing activities associated

with timber harvest and thinning increased risks

for the species considered. We assumed that watershed and riparian restoration, and livestock management would have positive net effects and provide the greatest benefits for species in watersheds

with the potential to respond. It was not clear,

however, how effective those activities would be in

restoring watershed and hydrologic processes.

Table 3.12. Summary of current known and predicted status of seven salmonid species versus ownership

and land management designation for each subwatershed. The data represent a summary of the current

status databases by management cluster as defined in Lee and others (1996).

Bull trout

Management

cluster'

BR

FG

FH

FM

FW

NP

PA

PF

PR

TL

Absent2

207

203

354

428

278

33

590

752

304

167

Depressed2

21

86

112

294

131

8

19

108

11

23

Strong2

2

46

17

34

155

2

2

7

2

3

Total

230

335

483

756

564

43

611

867

317

193

Percent

5.23

7.62

10.98

17.19

12.82

0.98

13.89

19.71

7.21

4.39

Total 3316 813 270 4399 100

'BR = BLM rangelands; FG = FS forest and rangeland, moderate impact, grazed; FH = FS forest, high impact, grazed; FM = FS forest, highmoderate impact, no grazing; FW = FS-managed wilderness; NP = NFS forestland; PA = Private agriculture; PF = Private land and FS forestland;

PR = Private and BLM rangeland; TL = Tribal lands.

2Known + predicted.

46$ Aquatics
Table 3.13. Summary of current known and predicted status of seven salmonid species versus ownership

and land management designation for each subwatershed. The data represent a summary of the current

status databases by management cluster as defined in Lee and others (1996).

Westslope cutthroat trout

Management

cluster'

BR

FG

FH

FM

FW

NP

PA

PF

PR

TL

Absent2

3

32

55

44

83

2

153

138

36

23

Depressed2

55

89

145

504

120

40

47

413

21

50

Strong2

4

68

40

154

277

0

0

38

1

5

Total

62

189

240

702

480

42

200

589

58

78

Percent

2.35

7.16

9.09

26.59

18.18

1.59

7.58

22.31

2.2

2.95

Total 569 1484 587 2640 100

'BR = BLM rangelands; FG = FS forest and rangeland, moderate impact, grazed; FH = FS forest, high impact, grazed; FM = FS forest, highmoderate impact, no grazing; FW = FS-managed wilderness; NP = NPS forestland; PA = Private agriculture; PF = Private land and FS forestland;

PR = Private and BLM rangeland; TL = Tribal lands.

'Known + predicted.

Table 3.14. Summary of current known and predicted status of seven salmonid species versus ownership and

land management designation for each subwatershed. The data represent a summary of the current status databases by management cluster as defined in Lee and others (1996).

Yellowstone cutthroat trout

Management

cluster1

BR

FG

FH

FM

FW

NP

PA

PF

PR

TL

Total

Absent2

28

4

25

7

0

1

75

10

61

19

230

Depressed2

2

44

20

4

8

1

45

35

12

2

173

Strong2

0

55

42

3

39

22

19

25

4

0

209

Total

30

103

87

14

47

24

139

70

77

21

612

Percent

4.9

16.83

14.22

2.29

7.68

3.92

22.71

11.44

12.58

3.43

100

'BR = BLM rangelands; FG = FS forest and rangeland, moderate impact, grazed; FH = FS forest, high impact, grazed; FM = FS forest, highmoderate impact, no grazing; FW = FS-managed wilderness; NP = NPS forestland; PA = Private agriculture; PF = Private land and FS forestland;

PR = Private and BLM rangeland; TL = Tribal lands.

'Known + predicted.

Aquatics 46?
Table 3.15. Summary of current known and predicted status of seven salmonid species versus ownership

and land management designation for each subwatershed. The data represent a summary of the current

status databases by management cluster as defined in Lee and others (1996).

Redband trout

Management

cluster1

BR

FG

FH

FM

FW

NP

PA

PF

PR

TL

Absent2

724

87

110

131

191

0

614

207

370

60

Depressed2

284

137

318

219

178

8

347

212

290

27

Strong2

36

126

202

13

75

0

13

245

19

86

Total

1044

350

630

363

444

8

974

664

679

173

Percent

19.59

6.57

11.82

6.81

8.33

0.15

18.28

12.46

12.74

3.25

Total 2494 2020 815 5329 100

'BR = BLM rangelands; FG = FS forest and rangeland, moderate impact, grazed; FH = FS forest, high impact, grazed; FM = FS forest, highmoderate impact, no grazing; FW = FS-managed wilderness; NP = NPS forestland; PA = Private agriculture; PF = Private land and FS forestland;

PR = Private and BLM rangeland; TL = Tribal lands.

'Known + predicted.

Table 3.16. Summary of current known and predicted status of seven salmonid species versus ownership

and land management designation for each subwatershed. The data represent a summary of the current

status databases by management cluster as defined in Lee and others (1996).

Steelhead trout

Management

cluster1

BR

FG

FH

FM

FW

NP

PA

PF

PR

TL

Absent2

729

122

231

78

69

0

216

238

268

66

Depressed2

31

155

214

166

277

0

205

188

142

53

Migration2

10

1

7

20

46

0

107

18

40

7

Strong2

0

5

8

1

2

0

2

2

0

3

Total

770

283

460

265

394

0

530

446

450

129

Percent

20.66

7.59

12.34

7.11

10.57

0

14.22

11.97

12.07

3.46

Total 2017 1431 256 23 3727 100

'BR = BLM rangelands; FG = FS forest and rangeland, moderate impact, grazed; FH = FS forest, high impact, grazed; FM = FS forest, high-moderate impact, no grazing; FW = FS-managed wilderness; NP = NPS forestland; PA = Private agriculture; PF = Private land and FS forestland; PR =

Private and BLM rangeland; TL = Tribal lands.

2Known + predicted.

468 Aquatics
Table 3.17. Summary of current known and predicted status of seven salmonid species versus ownership

and land management designation for each subwatershed. The data represent a summary of the current

status databases by management cluster as defined in Lee and others (1996).

Stream-type Chinook salmon

Management

cluster1

BR

FG

FH

FM

FW

NP

PA

PF

PR

TL

Total

Absent2

721

168

291

130

165

0

332

301

316

67

2491

Depressed2

10

91

117

111

168

0

45

79

28

19

668

Migration2

18

10

9

19

47

0

105

23

49

1

281

Strong2

0

1

3

0

3

0

0

1

0

0

8

Total

749

270

420

260

383

0

482

404

393

87

3448

Percent

21.72

7.83

12.18

7.54

11.11

0

13.98

11.72

11.40

2.52

100

'BR = BLM rangelands; FG = FS forest and rangeland, moderate impact, grazed; FH = FS forest, high impact, grazed; FM = FS forest, high-moderate impact, no grazing; FW = FS-managed wilderness; NP = NFS forestland; PA = Private agriculture; PF = Private land and FS forestland; PR =

Private and BLM rangeland; TL = Tribal lands.

:Known + predicted.

Table 3.18. Summary of current known and predicted status of seven salmonid species versus ownership

and land management designation for each subwatershed. The data represent a summary of the current

status databases by management cluster as defined in Lee and others (1996).

Ocean-type Chinook salmon

Management

cluster1

BR

FG

FH

FM

FW

NP

PA

PF

PR

TL

Total

Absent2

21

19

36

12

19

0

89

68

72

50

386

Depressed2

0

2

4

3

8

0

21

14

15

4

71

Migration2

0

0

0

0

0

0

43

11

9

1

64

Strong2

0

1

0

2

0

0

5

8

5

0

21

Total

21

22

40

17

27

0

158

101

101

55

542

Percent

3.87

4.06

7.38

3.14

4.98

0

29.15

18.63

18.63

10.15

100

'BR = BLM rangelands; FG = FS forest and rangeland, moderate impact, grazed; FH = FS forest, high impact, grazed; FM = FS forest, high-moderate impact, no grazing; FW = FS-managed wilderness; NP = NFS forestland; PA = Private agriculture; PF = Private land and FS forestland; PR =

Private and BLM rangeland; TL = Tribal lands.

2Known + predicted.

Aquatics 469